Specify the following parameters to retrieve the required data from CMAP. Here we download variable of interest aggregated at varying depth.

Use getAggregatedTableData to download required data.

Call plot_depth function to obtain plot_ly/ggplot object.

Example I

con <- dbConnect(odbc::odbc(), DSN="CMAP-MSSQL",UID="ArmLab",PWD="ArmLab2018")
#
# Inpit variable:
table.list <- c('tblArgoMerge_REP', 'tblPisces_NRT', 'tblDarwin_Chl_Climatology') 
var.list <-  c('argo_merge_chl_adj', 'CHL', 'chl01_darwin_clim')  
#
selIndex <- 1                                    # selected argo_merge_chl_adj from tblArgoMerge_REP 
table.name <- table.list[selIndex]
sel.var <- var.list[selIndex]  
#
range.var <- list()
range.var$lat <- c(20,24)
range.var$lon <- c( -170, -150)
range.var$depth <- c(0, 1500)
range.var$time <- c('2016-04-30', '2016-04-30')


## Subset selection: data retrieval
agg.var <- 'depth' 
tbl.subset <- getAggregatedTableData(con, table.name, sel.var, range.var, agg.var)
head(tbl.subset)
## # A tibble: 6 x 2
##   depth argo_merge_chl_adj
##   <dbl>              <dbl>
## 1  4.10            NA     
## 2  4.20            NA     
## 3  5.90            NA     
## 4  6               NA     
## 5  7.20             0.0180
## 6  7.80            NA
## Plot -- Depth profiles:
p <- plot_depth(tbl.subset, 'plotly',sel.var)
p
dbDisconnect(con)